SoroushVahidi/scidocs huggingface dataset:
Visual Exploration of Climate Variability Changes Using Wavelet Analysis
(2009)

Due to its nonlinear nature, the climate system shows quite high natural variability on different time scales, including multiyear oscillations such as the El Nino southern oscillation phenomenon. Beside a shift of the mean states and of extreme values of climate variables, climate change may also change the frequency or the spatial patterns of these natural climate variations. Wavelet analysis is a well established tool to investigate variability in the frequency domain. However, due to the size and complexity of the analysis results, only few time series are commonly analyzed concurrently. In this paper we will explore different techniques to visually assist the user in the analysis of variability and variability changes to allow for a holistic analysis of a global climate model data set consisting of several variables and extending over 250 years. Our new framework and data from the IPCC AR4 simulations with the coupled climate model ECHAM5/MPI-OM are used to explore the temporal evolution of El Nino due to climate change.
Highly reliable M1X MLC NAND flash memory cell with novel active air-gap and p+ poly process integration technologies
(2013)

Our Middle-1X nm MLC NAND (M1X) flash cell is intensively characterized with respect to reliability and manufacturability. For the first time, the novel active air-gap technology is applied to alleviate the drop of channel boosting potential of program inhibition mode, BL-BL interference is reduced to our 2y nm node level by this novel integration technology. Furthermore, it also relaxes the effect of process variation like EFH (Effective Field oxide Height) on cell Vt distribution. Better endurance and retention characteristics can be obtained by p+ doped poly gate. By optimization of active air-gap profile and poly doping level, M1X nm MLC NAND flash memory has been successfully implemented with superior manufacturability and acceptable reliability.
Non-sentential Question Resolution using Sequence to Sequence Learning
(2016)

An interactive Question Answering (QA) system frequently encounters non-sentential (incomplete) questions. These non-sentential questions may not make sense to the system when a user asks them without the context of conversation. The system thus needs to take into account the conversation context to process the incomplete question. In this work, we present a recurrent neural network (RNN) based encoder decoder network that can generate a complete (intended) question, given an incomplete question and conversation context. RNN encoder decoder networks have been show to work well when trained on a parallel corpus with millions of sentences, however it is extremely hard to obtain conversation data of this magnitude. We therefore propose to decompose the original problem into two separate simplified problems where each problem focuses on an abstraction. Specifically, we train a semantic sequence model to learn semantic patterns, and a syntactic sequence model to learn linguistic patterns. We further combine syntactic and semantic sequence models to generate an ensemble model. Our model achieves a BLEU score of 30.15 as compared to 18.54 using a standard RNN encoder decoder model.
Development of an Omni-Directional Mobile Robot with 3 DOF Decoupling Drive Mechanism
(1995)

A ne'ui driving mech,anism for holonomic ornwidirectional mobi le robots i s designzed, ,which enu.bles 3 DOF m o t i o n control by three correspondent actuators in, (I decozipled ma'nner ,with n o redundan,cy. A prototype of the omni-drrectional mobile robot w i th th,e dr iu ing mechan i sm is developed including a parallel link suspemion m,echanism. T h e k inemat ics of th.e omnidirectionsal mobile robot i s also analyzed, and simulat i o n fo,r velocity control of the robot is perform.ed by od f o r ,oelocity modula t ion wi th in,terpolation. to uchieve the given target pos i t ion and velocity.
Residential exposure to aircraft noise and hospital admissions for cardiovascular diseases: multi-airport retrospective study
(2013)

OBJECTIVE
To investigate whether exposure to aircraft noise increases the risk of hospitalization for cardiovascular diseases in older people (≥ 65 years) residing near airports.


DESIGN
Multi-airport retrospective study of approximately 6 million older people residing near airports in the United States. We superimposed contours of aircraft noise levels (in decibels, dB) for 89 airports for 2009 provided by the US Federal Aviation Administration on census block resolution population data to construct two exposure metrics applicable to zip code resolution health insurance data: population weighted noise within each zip code, and 90th centile of noise among populated census blocks within each zip code.


SETTING
2218 zip codes surrounding 89 airports in the contiguous states.


PARTICIPANTS
6 027 363 people eligible to participate in the national medical insurance (Medicare) program (aged ≥ 65 years) residing near airports in 2009.


MAIN OUTCOME MEASURES
Percentage increase in the hospitalization admission rate for cardiovascular disease associated with a 10 dB increase in aircraft noise, for each airport and on average across airports adjusted by individual level characteristics (age, sex, race), zip code level socioeconomic status and demographics, zip code level air pollution (fine particulate matter and ozone), and roadway density.


RESULTS
Averaged across all airports and using the 90th centile noise exposure metric, a zip code with 10 dB higher noise exposure had a 3.5% higher (95% confidence interval 0.2% to 7.0%) cardiovascular hospital admission rate, after controlling for covariates.


CONCLUSIONS
Despite limitations related to potential misclassification of exposure, we found a statistically significant association between exposure to aircraft noise and risk of hospitalization for cardiovascular diseases among older people living near airports.
Continuous Requirements Engineering and Human-Centered Agile Software Development
(2016)

The idea of Continuous Requirements Engineering in relation to a Human-Centered Agile Development Process is discussed. First, it is argued that Continuous Requirements Engineering has to cover design-time and runtime aspects. In this way maintenance is covered as well. Second, arguments are provided for integrating aspects of usability and user experience into requirements specifications. This has to be done continuously. Therefore, the term Continuous Human-Centered Development is introduced and discussed. Based on a process model for SCRUM some aspects of integrating HCD into the development process are discussed.
From Non-Functional Requirements to Design through Patterns
(2001)

Design patterns aid in documenting and communicating proven design solutions to recurring problems. They describe not only how to solve design problems, but also why a solution is chosen over others and what trade-offs are made. Non-functional requirements (NFRs) are pervasive in descriptions of design patterns. They play a crucial role in understanding the problem being addressed, the trade-offs discussed, and the design solution proposed. However, since design patterns are mostly expressed as informal text, the structure of the design reasoning is not systematically organised. This paper proposes a systematic treatment of NFRs in descriptions of patterns and when applying patterns during design. The approach organises, analyses and refines non-functional requirements, and provides guidance and reasoning support when applying patterns during the design of a software system. Three design patterns taken from the literature are used to illustrate this approach.
Tools for ontology matching practical considerations
(2016)

There exists a large body of scienti c literature devoted to ontology matching, aligning, mapping translating and merging. With it, comes a long list (90+) of tools that support various aspects of these operations. We have approached such tools from the perspective of the INTER-IoT project, in which one of the goals is to facilitate semantic interoperability of Internet of Things platforms. Thus, we had to answer a question: what is actually available when one needs to align/merge ontologies. Here, we summarize our ndings.
Speedy transactions in multicore in-memory databases
(2013)

Silo is a new in-memory database that achieves excellent performance and scalability on modern multicore machines. Silo was designed from the ground up to use system memory and caches efficiently. For instance, it avoids all centralized contention points, including that of centralized transaction ID assignment. Silo's key contribution is a commit protocol based on optimistic concurrency control that provides serializability while avoiding all shared-memory writes for records that were only read. Though this might seem to complicate the enforcement of a serial order, correct logging and recovery is provided by linking periodically-updated epochs with the commit protocol. Silo provides the same guarantees as any serializable database without unnecessary scalability bottlenecks or much additional latency. Silo achieves almost 700,000 transactions per second on a standard TPC-C workload mix on a 32-core machine, as well as near-linear scalability. Considered per core, this is several times higher than previously reported results.
To Lock, Swap, or Elide: On the Interplay of Hardware Transactional Memory and Lock-Free Indexing
(2015)

The release of hardware transactional memory (HTM) in commodity CPUs has major implications on the design and implementation of main-memory databases, especially on the architecture of highperformance lock-free indexing methods at the core of several of these systems. This paper studies the interplay of HTM and lockfree indexing methods. First, we evaluate whether HTM will obviate the need for crafty lock-free index designs by integrating it in a traditional B-tree architecture. HTM performs well for simple data sets with small fixed-length keys and payloads, but its benefits disappear for more complex scenarios (e.g., larger variable-length keys and payloads), making it unattractive as a general solution for achieving high performance. Second, we explore fundamental differences between HTM-based and lock-free B-tree designs. While lock-freedom entails design complexity and extra mechanism, it has performance advantages in several scenarios, especially high-contention cases where readers proceed uncontested (whereas HTM aborts readers). Finally, we explore the use of HTM as a method to simplify lock-free design. We find that using HTM to implement a multi-word compare-and-swap greatly reduces lockfree programming complexity at the cost of only a 10-15% performance degradation. Our study uses two state-of-the-art index implementations: a memory-optimized B-tree extended with HTM to provide multi-threaded concurrency and the Bw-tree lock-free B-tree used in several Microsoft production environments.
An effective hybrid transactional memory system with strong isolation guarantees
(2007)

We propose signature-accelerated transactional memory (SigTM), ahybrid TM system that reduces the overhead of software transactions. SigTM uses hardware signatures to track the read-set and write-set forpending transactions and perform conflict detection between concurrent threads. All other transactional functionality, including dataversioning, is implemented in software. Unlike previously proposed hybrid TM systems, SigTM requires no modifications to the hardware caches, which reduces hardware cost and simplifies support for nested transactions and multithreaded processor cores. SigTM is also the first hybrid TM system to provide strong isolation guarantees between transactional blocks and non-transactional accesses without additional read and write barriers in non-transactional code.
 Using a set of parallel programs that make frequent use of coarse-grain transactions, we show that SigTM accelerates software transactions by 30% to 280%. For certain workloads, SigTM can match the performance of a full-featured hardware TM system, while for workloads with large read-sets it can be up to two times slower. Overall, we show that SigTM combines the performance characteristics and strong isolation guarantees of hardware TM implementations with the low cost and flexibility of software TM systems.
The End of an Architectural Era (It's Time for a Complete Rewrite)
(2007)

In previous papers [SC05, SBC+07], some of us predicted the end of “one size fits all” as a commercial relational DBMS paradigm. These papers presented reasons and experimental evidence that showed that the major RDBMS vendors can be outperformed by 1-2 orders of magnitude by specialized engines in the data warehouse, stream processing, text, and scientific database markets. Assuming that specialized engines dominate these markets over time, the current relational DBMS code lines will be left with the business data processing (OLTP) market and hybrid markets where more than one kind of capability is required. In this paper we show that current RDBMSs can be beaten by nearly two orders of magnitude in the OLTP market as well. The experimental evidence comes from comparing a new OLTP prototype, H-Store, which we have built at M.I.T., to a popular RDBMS on the standard transactional benchmark, TPC-C. We conclude that the current RDBMS code lines, while attempting to be a “one size fits all” solution, in fact, excel at nothing. Hence, they are 25 year old legacy code lines that should be retired in favor of a collection of “from scratch” specialized engines. The DBMS vendors (and the research community) should start with a clean sheet of paper and design systems for tomorrow’s requirements, not continue to push code lines and architectures designed for yesterday’s needs.
Biped gait controller for large speed variations, combining reflexes and a central pattern generator in a neuromuscular model
(2015)

Controllers based on neuromuscular models hold the promise of energy-efficient and human-like walkers. However, most of them rely on optimizations or cumbersome hand-tuning to find controller parameters which, in turn, are usually working for a specific gait or forward speed only. Consequently, designing neuromuscular controllers for a large variety of gaits is usually challenging and highly sensitive. In this contribution, we propose a neuromuscular controller combining reflexes and a central pattern generator able to generate gaits across a large range of speeds, within a single optimization. Applying this controller to the model of COMAN, a 95 cm tall humanoid robot, we were able to get energy-efficient gaits ranging from 0.4 m/s to 0.9 m/s. This covers normal human walking speeds once scaled to the robot height. In the proposed controller, the robot speed could be continuously commanded within this range by changing three high-level parameters as linear functions of the target speed. This allowed large speed transitions with no additional tuning. By combining reflexes and a central pattern generator, this approach can also predict when the next strike will occur and modulate the step length to step over a hole.
Using Argument Mining to Assess the Argumentation Quality of Essays
(2016)

Argument mining aims to determine the argumentative structure of texts. Although it is said to be crucial for future applications such as writing support systems, the benefit of its output has rarely been evaluated. This paper puts the analysis of the output into the focus. In particular, we investigate to what extent the mined structure can be leveraged to assess the argumentation quality of persuasive essays. We find insightful statistical patterns in the structure of essays. From these, we derive novel features that we evaluate in four argumentation-related essay scoring tasks. Our results reveal the benefit of argument mining for assessing argumentation quality. Among others, we improve the state of the art in scoring an essay’s organization and its argument strength.
Ontology-Aware Token Embeddings for Prepositional Phrase Attachment
(2017)

Type-level word embeddings use the same set of parameters to represent all instances of a word regardless of its context, ignoring the inherent lexical ambiguity in language. Instead, we embed semantic concepts (or synsets) as defined in WordNet and represent a word token in a particular context by estimating a distribution over relevant semantic concepts. We use the new, context-sensitive embeddings in a model for predicting prepositional phrase (PP) attachments and jointly learn the concept embeddings and model parameters. We show that using context-sensitive embeddings improves the accuracy of the PP attachment model by 5.4% absolute points, which amounts to a 34.4% relative reduction in errors.
Developing an Isolated Word Recognition System in MATLAB
(2009)

The Development Workflow There are two major stages within isolated word recognition: a training stage and a testing stage. Training involves “teaching” the system by building its dictionary, an acoustic model for each word that the system needs to recognize. In our example, the dictionary comprises the digits ‘zero’ to ‘nine’. In the testing stage we use acoustic models of these digits to recognize isolated words using a classification algorithm. The development workflow consists of three steps: Speech acquisition • Speech analysis • User interface development •
Ruminating Reader: Reasoning with Gated Multi-Hop Attention
(2017)

To answer the question in machine comprehension (MC) task, the models need to establish the interaction between the question and the context. To tackle the problem that the single-pass model cannot reflect on and correct its answer, we present Ruminating Reader. Ruminating Reader adds a second pass of attention and a novel information fusion component to the Bi-Directional Attention Flow model (BIDAF). We propose novel layer structures that construct a query aware context vector representation and fuse encoding representation with intermediate representation on top of BIDAF model. We show that a multi-hop attention mechanism can be applied to a bi-directional attention structure. In experiments on SQuAD, we find that the Reader outperforms the BIDAF baseline by 2.1 F1 score and 2.7 EM score. Our analysis shows that different hops of the attention have different responsibilities in selecting answers.
An investigation of current models of second language speech perception: the case of Japanese adults' perception of English consonants.
(2000)

This study reports the results of two experiments with native speakers of Japanese. In experiment 1, near-monolingual Japanese listeners participated in a cross-language mapping experiment in which they identified English and Japanese consonants in terms of a Japanese category, then rated the identifications for goodness-of-fit to that Japanese category. Experiment 2 used the same set of stimuli in a categorial discrimination test. Three groups of Japanese speakers varying in English-language experience, and one group of native English speakers participated. Contrast pairs composed of two English consonants, two Japanese consonants, and one English and one Japanese consonant were tested. The results indicated that the perceived phonetic distance of second language (L2) consonants from the closest first language (L1) consonant predicted the discrimination of L2 sounds. In addition, this study investigated the role of experience in learning sounds in a second language. Some of the consonant contrasts tested showed evidence of learning (i.e., significantly higher scores for the experienced than the relatively inexperienced Japanese groups). The perceived phonetic distance of L1 and L2 sounds was found to predict learning effects in discrimination of L1 and L2 sounds in some cases. The results are discussed in terms of models of cross-language speech perception and L2 phonetic learning.
Resource Sharing in Continuous Sliding-Window Aggregates
(2004)

We consider the problem of resource sharing when processing large numbers of continuous queries. We specifically address sliding-window aggregates over data streams, an important class of continuous operators for which sharing has not been addressed. We present a suite of sharing techniques that cover a wide range of possible scenarios: different classes of aggregation functions (algebraic, distributive, holistic), different window types (time-based, tuple-based, suffix, historical), and different input models (single stream, multiple substreams). We provide precise theoretical performance guarantees for our techniques, and show their practical effectiveness through experimental study.
Design of Wireless Sensor System for Neonatal Monitoring
(2011)

In this paper, we present the application of wireless sensor technology and the advantages it will inherently have for neonatal care and monitoring at Neonatal Intensive Care Units (NICU). An electrocardiography (ECG) readout board and a wireless transceiver module developed by IMEC at the Holst Centre in the Netherlands are embedded in the proposed wireless sensor systems in combination with the signal processing and software interface developed at the Department of Industrial Design, Eindhoven University of Technology (TU/e). Through development of this prototype system, we opt to ensure correct data transmission, detection and display. The wireless system is designed to be suitable for integration into non-invasive monitoring platforms such as a smart neonatal jacket developed at TU/e. Experiments at Maxima Medical Centre (MMC) in Veldhoven, the Netherlands demonstrate the wireless transmission of ECG data from the smart jacket integrated with textile electrodes.
Sentiment Analysis and Subjectivity
(2010)

Textual information in the world can be broadly categorized into two main types: facts and opinions. Facts are objective expressions about entities, events and their properties. Opinions are usually subjective expressions that describe people’s sentiments, appraisals or feelings toward entities, events and their properties. The concept of opinion is very broad. In this chapter, we only focus on opinion expressions that convey people’s positive or negative sentiments. Much of the existing research on textual information processing has been focused on mining and retrieval of factual information, e.g., information retrieval, Web search, text classification, text clustering and many other text mining and natural language processing tasks. Little work had been done on the processing of opinions until only recently. Yet, opinions are so important that whenever we need to make a decision we want to hear others’ opinions. This is not only true for individuals but also true for organizations.
Comparison of Classifier Fusion Methods for Classification in Pattern Recognition Tasks
(2006)

This work presents a comparison of current research in the use of voting ensembles of classifiers in order to improve the accuracy of single classifiers and make the performance more robust against the difficulties that each individual classifier may have. Also, a number of combination rules are proposed. Different voting schemes are discussed and compared in order to study the performance of the ensemble in each task. The ensembles have been trained on real data available for benchmarking and also applied to a case study related to statistical description models of melodies for music genre recognition.